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KBSE
1997
IEEE
13 years 10 months ago
Genetic Algorithms for Dynamic Test Data Generation
In software testing, it is often desirable to find test inputs that exercise specific program features. To find these inputs by hand is extremely time-consuming, especially whe...
Christoph C. Michael, Gary McGraw, Michael Schatz,...
CEC
2009
IEEE
14 years 16 days ago
An evaluation of Differential Evolution in software test data generation
— One of the main tasks software testing involves is the generation of the test inputs to be used during the test. Due to its expensive cost, the automation of this task has beco...
Ricardo Landa Becerra, Ramón Sagarna, Xin Y...
ICST
2010
IEEE
13 years 3 months ago
Automated Test Data Generation on the Analyses of Feature Models: A Metamorphic Testing Approach
A Feature Model (FM) is a compact representation of all the products of a software product line. The automated extraction of information from FMs is a thriving research topic invo...
Sergio Segura, Robert M. Hierons, David Benavides,...
SIGSOFT
2007
ACM
14 years 6 months ago
The impact of input domain reduction on search-based test data generation
There has recently been a great deal of interest in search? based test data generation, with many local and global search algorithms being proposed. However, to date, there has be...
Mark Harman, Youssef Hassoun, Kiran Lakhotia, Phil...
KBSE
2007
IEEE
14 years 1 days ago
Nighthawk: a two-level genetic-random unit test data generator
Randomized testing has been shown to be an effective method for testing software units. However, the thoroughness of randomized unit testing varies widely according to the settin...
James H. Andrews, Felix Chun Hang Li, Tim Menzies